INDUSTRY SOLUTIONS

Phishing Protection for Financial Services

Protect your business from phishing attacks with INKY's next-generation email security solution.

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Why and How do Phishers Target Financial Institutions?

Accelerated by the pandemic, banking has moved almost entirely online and is likely to stay that way. Online access provides a thousand avenues phishers can pursue in their quest to despoil people of money. And financial institutions provide a perfectly fungible commodity: money. Once phishers pilfer it, it disappears in the night.

In addition, financial institutions interact with a wide array of other individuals and institutions. In sum, banks are where the money is, there's lots of interaction between people who don't necessarily know each other well, and security systems and protocols are uneven at best. An attack starts with a phishing email, sent, perhaps, from a trusted but hijacked account known to the recipient, maybe impersonating a trusted brand or person in the company's own hierarchy. 

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How are Financial Institutions Currently Protected?

At the moment, most financial institutions deliver their email through either their own on-premise Exchange server or a secure email gateway (SEG) provider — including but not limited to Microsoft, Proofpoint, and Mimecast. These services have only rudimentary protection against phishing. Phishing attacks are like nuclear missile sallies. It’s not enough to stop 99% of them; it has to be 100%.

In the tight window between when an email server receives a mail and when it has to deliver it to a recipient’s inbox, the SEGs can only examine the universal email tests (DKIM and SPF), take a cursory look at the nature of the message with regular expression matching, and look up the sender’s address on whatever bad lists they have on the shelf. With this limited examination, they can't spot the phish. And this is the best case. Most can’t run their full analysis stack on every email because it takes too long.

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How Does INKY Stop Phishing Attacks on Financial Institutions?

INKY sits downstream from the SEG and spends less than two seconds looking at an email before dropping it in the recipient’s inbox. From this privileged position, INKY catches all the phish that get past the SEGs (proof that they’re not catching them and we are). Recently, INKY processed its billionth email. It's seen a lot of phish they missed.

What INKY does during that two seconds is release a swarm of mathematical models on the email’s raw HTML code. They all operate simultaneously on it, testing for this and that (our secret sauce), and formulating an “opinion,” which is in fact a number on a scale, representing the results of its particular test.

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Real-time phishing awareness training.

One more model takes the output of all the rest and comes up with an overall score that represents how bad INKY thinks the email is. This value is interpreted to create a colored banner, which is inserted in the email before it's passed on to the recipient’s inbox (and pulled back out of any reply on the way out).

Beyond a certain threshold of badness, the banner is red. Suspicious, maybe spam, but not necessarily outright dangerous? Yellow. Neutral gray means no thresholds were triggered.

The banners also have feedback links that allow the recipient to correct INKY (e.g., That’s not spam; that's my Wall Street Journal subscription!). When an authenticated INKY user designates something spam in the feedback dialog, they have the opportunity to block the sender — or even the sender’s entire domain, a favorite feature of many customers.

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Can you rely on your end-users to be on high-alert for all of these phishing tactics across all devices?

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Brand Hijacking

Detect brand-indicative and scam-indicative images using computer vision models.

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Text Anomalies

Find brand-indicative and scam-indicative text using approximate matching.

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Brand Impersonation

Determine the apparent brand using color palette, layout features, prominent text, and more.

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Zero Font

Pinpoint zero-font and other forms or hidden text.

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Text Cloaking

Identify Unicode homographs, typos, and other text cloaking.

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